Scatter Pie plot

set.seed(123)
long <- rnorm(50, sd=100)
lat <- rnorm(50, sd=50)
d <- data.frame(long=long, lat=lat)
d <- with(d, d[abs(long) < 150 & abs(lat) < 70,])
n <- nrow(d)
d$region <- factor(1:n)
d$A <- abs(rnorm(n, sd=1))
d$B <- abs(rnorm(n, sd=2))
d$C <- abs(rnorm(n, sd=3))
d$D <- abs(rnorm(n, sd=4))
d[1, 4:7] <- d[1, 4:7] * 3
head(d)
##          long        lat region          A        B        C        D
## 1  -56.047565  12.665926      1 2.13121969 8.663359 3.928711 8.676792
## 2  -23.017749  -1.427338      2 0.25688371 1.403569 1.375096 4.945092
## 4    7.050839  68.430114      3 0.24669188 0.524395 3.189978 5.138863
## 5   12.928774 -11.288549      4 0.34754260 3.144288 3.789556 2.295894
## 8 -126.506123  29.230687      5 0.95161857 3.029335 1.048951 2.471943
## 9  -68.685285   6.192712      6 0.04502772 3.203072 2.596539 4.439393
ggplot() + geom_scatterpie(aes(x=long, y=lat, group=region), data=d,
                           cols=LETTERS[1:4]) + coord_equal()

d$radius <- 6 * abs(rnorm(n))
p <- ggplot() + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius), data=d,
                                cols=LETTERS[1:4], color=NA) + coord_equal()
p + geom_scatterpie_legend(d$radius, x=-140, y=-70)

The geom_scatterpie is especially useful for visualizing data on a map.

world <- map_data('world')
p <- ggplot(world, aes(long, lat)) +
    geom_map(map=world, aes(map_id=region), fill=NA, color="black") +
    coord_quickmap()
p + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius),
                    data=d, cols=LETTERS[1:4], color=NA, alpha=.8) +
    geom_scatterpie_legend(d$radius, x=-160, y=-55)

p + geom_scatterpie(aes(x=long, y=lat, group=region, r=radius),
                    data=d, cols=LETTERS[1:4], color=NA, alpha=.8) +
    geom_scatterpie_legend(d$radius, x=-160, y=-55, n=3, labeller=function(x) 1000*x^2)

Session info

Here is the output of sessionInfo() on the system on which this document was compiled:

## R version 4.0.2 (2020-06-22)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Arch Linux
## 
## Matrix products: default
## BLAS:   /usr/lib/libblas.so.3.9.0
## LAPACK: /usr/lib/liblapack.so.3.9.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] scatterpie_0.1.5 ggplot2_3.3.2   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.5          BiocManager_1.30.10 pillar_1.4.6       
##  [4] compiler_4.0.2      prettydoc_0.4.0     tools_4.0.2        
##  [7] digest_0.6.25       evaluate_0.14       lifecycle_0.2.0    
## [10] tibble_3.0.3        gtable_0.3.0        pkgconfig_2.0.3    
## [13] rlang_0.4.7         rvcheck_0.1.8       yaml_2.2.1         
## [16] xfun_0.16           withr_2.2.0         stringr_1.4.0      
## [19] dplyr_1.0.2         knitr_1.29          maps_3.3.0         
## [22] generics_0.0.2      vctrs_0.3.4         grid_4.0.2         
## [25] tidyselect_1.1.0    glue_1.4.2          R6_2.4.1           
## [28] rmarkdown_2.3       polyclip_1.10-0     tidyr_1.1.2        
## [31] farver_2.0.3        purrr_0.3.4         tweenr_1.0.1       
## [34] magrittr_1.5        scales_1.1.1        ellipsis_0.3.1     
## [37] htmltools_0.5.0     MASS_7.3-52         ggforce_0.3.2      
## [40] colorspace_1.4-1    labeling_0.3        stringi_1.4.6      
## [43] munsell_0.5.0       crayon_1.3.4